---
name: Google BigQuery
menu: Connecting to Databases
route: /docs/databases/bigquery
index: 16
version: 1
---

## Google BigQuery

The recommended connector library for BigQuery is
[pybigquery](https://github.com/mxmzdlv/pybigquery).

The connection string for BigQuery looks like:

```
bigquery://{project_id}
```

When adding a new BigQuery connection in Superset, you'll also need to add the GCP Service Account
credentials file (as a JSON).

1. Create your Service Account via the Google Cloud Platform control panel, provide it access to the
   appropriate BigQuery datasets, and download the JSON configuration file for the service account.

2. n Superset, Add a JSON blob to the **Secure Extra** field in the database configuration form with
   the following format:

```
{
    "credentials_info": <contents of credentials JSON file>
}
```

The resulting file should have this structure:

```
{
    "credentials_info": {
        "type": "service_account",
        "project_id": "...",
        "private_key_id": "...",
        "private_key": "...",
        "client_email": "...",
        "client_id": "...",
        "auth_uri": "...",
        "token_uri": "...",
        "auth_provider_x509_cert_url": "...",
        "client_x509_cert_url": "...",
    }
}
```

You should then be able to connect to your BigQuery datasets.

To be able to upload CSV or Excel files to BigQuery in Superset, you'll need to also add the
[pandas_gbq](https://github.com/pydata/pandas-gbq) library.
